This master's thesis explores the impact of culturally reflexive AI on pregnancy care, aiming to address the maternal health crisis in the United States. It recognizes historical biases affecting Black women in healthcare and critiques the perpetuation of racist paradigms in AI technologies, spotlighting three specific software solutions.

The objective was to promote culturally reflexive AI development in maternal health by proposing a framework based on the four cornerstones of Responsible Innovation: anticipation, inclusivity, reflexivity, and responsiveness.

The thesis suggests integrating cultural reflexivity into AI technology for maternal health, emphasizing responsible innovation. Specific AI technologies are introduced as examples of efforts to mitigate embedded racist paradigms in healthcare.

Conclusions:

The thesis highlights the increasing prevalence of AI algorithms in healthcare and underscores the importance of their responsible development. The ultimate goal is to identify a pathway toward accessible and equitable care for all, especially within the vulnerable context of pregnancy. The conclusion recommends future research involving experimentation, education, and on-site fieldwork to understand emotional responses and trust in AI applications in pregnancy care.

In summary, this thesis addresses historical biases, introduces AI solutions, and advocates for responsible and culturally reflexive AI development to tackle the maternal health crisis in the United States.